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» Learning and Classification of Complex Dynamics
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JMLR
2010
147views more  JMLR 2010»
13 years 2 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch
SAC
2006
ACM
14 years 1 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
NIPS
2004
13 years 9 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
ICMCS
2009
IEEE
132views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Video face recognition with graph-based semi-supervised learning
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
Effrosini Kokiopoulou, Pascal Frossard
ECAI
2004
Springer
14 years 1 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic